Overview

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This course features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. In this course, you'll dive into AWS's powerful data services and tools for modern workloads. Starting with Amazon RDS, you'll explore how to set up and manage relational databases on AWS. You'll also gain an understanding of advanced AWS database solutions, such as Aurora, DynamoDB, Redshift, and ElastiCache. Each of these services is tailored to different use cases, allowing you to choose the right database solution for your applications. Next, the course covers AWS Route 53 for DNS and domain management, enabling you to ensure high availability and failover capabilities for your websites and services. You will also explore Application Integration Services, including SNS, MQ, SQS, Step Functions, and SWF—all designed to integrate and coordinate your applications and workflows seamlessly. The course also dives into AWS's powerful Analytics tools like Athena, Kinesis, Elasticsearch, Glue, and QuickSight, which help you analyze large datasets, stream real-time data, and create insightful visualizations. You’ll also explore how Machine Learning services such as Rekognition, Polly, Translate, Transcribe, Comprehend, and SageMaker empower developers to build intelligent, scalable applications with advanced capabilities like image recognition, translation, text-to-speech, and NLP. This course is perfect for developers, data engineers, and professionals looking to expand their knowledge of AWS and modern data and machine learning workloads. While no formal prerequisites are required, familiarity with basic cloud computing concepts is beneficial. The course is designed for an intermediate skill level, ideal for those who want to level up their knowledge of AWS data services and machine learning tools. By the end of the course, you will be able to deploy, manage, and integrate databases on AWS, set up and use analytics and machine learning services, and design modern, scalable cloud workloads using AWS tools.

Syllabus

AWS Database Services

In this module, we will introduce AWS database services, focusing on Amazon RDS and its use for managing relational databases. You’ll also gain hands-on experience with database creation and learn about other advanced database solutions like Aurora, DynamoDB, and Redshift. By the end, you’ll understand how to choose the right database service based on application needs and scalability requirements.

Amazon Route 53

In this module, we will explore Amazon Route 53, AWS’s scalable and highly available DNS web service. You’ll learn how to configure Route 53 for domain registration, routing policies, and ensuring failover mechanisms. By the end, you'll be equipped to manage the DNS needs of your web applications effectively.

Application Integration Services

In this module, we will dive into AWS’s application integration services, starting with Amazon SNS for notifications, and moving to Amazon MQ and SQS for managing message-based workflows. Additionally, we’ll explore AWS Step Functions and SWF to streamline and orchestrate complex application workflows. You’ll gain the tools needed to integrate your applications efficiently on AWS.

Analytics

In this module, we will explore AWS analytics services, from querying data in Amazon S3 using Amazon Athena to processing real-time data streams with Amazon Kinesis. You’ll also gain insights into Amazon Glue for ETL processes and Amazon QuickSight for data visualizations. By the end, you’ll be prepared to leverage these tools for advanced data analytics in the cloud.

Machine Learning on AWS

In this module, we will introduce you to machine learning services on AWS, starting with Amazon Rekognition for analyzing images and videos. You’ll explore Amazon Polly for building speech-enabled applications and learn about Amazon SageMaker for end-to-end machine learning model development. This module will provide you with the foundational knowledge to integrate machine learning into your AWS applications.